Relating basic research on simple nervous systems of lower animals to applied research on higher vertebrates such as humans requires sophisticated comparative techniques. A new cross-correlational method based on information theory that produces a network connection structure from standard neuronal recordings will be tested, first by computer simulation and then with a real biological network, the swimming network of the seaslug Tritonia diomedea. Results of this analysis will then be used to construct a realistic computer model of the swimming network. The study of neural mechanisms of pattern formation, especially rhythmic patterns, is already a cornerstone of neuroethology. However, relatively less is known about how these networks are initiated and terminated. The long-term objective of this work is to use comparative computational techniques such as cross correlation and computer modeling to develop general principles of how rhythmic neural networks are turned on and off.